Alzheimer's disease and frontotemporal dementia are differentiated by discriminant analysis applied to 99(m)Tc HmPAO SPECT data

Objective-Alzheimer's disease (AD) and frontotemporal dementia (FTD) are th e most frequent neurodegenerative cognitive disorders. However, FTD remains poorly recognised clinically. The use of (99m)HmPAO-single photon emission computed tomography (SPECT) has been demonstrated in the differentiation o f AD and FTD. Nethertheless, there are very few comparative studies designe d to assess its precise value in this differential diagnosis. The aim was t o determine a simple decision rule, deduced from statistical analysis, whic h, if applied to regions of interest (ROIs) and mini mental state examinati on (MMSE), could improve the predictive value of SPECT in differential diag nosis between AD and FTD. Methods-Forty patients, 20 with probable AD and 20 with probable FTD were i ncluded. All patients underwent brain SPECT imaging, after an intravenous i njection of Tc-99m HmPAO-(555mBq). For each patient, 20 ROIs were determine d on the Fleishig's slice and their activity was normalised to the mean cer ebellar activity. Bivariate analysis (Wilcoxon rank tests) and multivariate analysis (stepwise discriminant analysis) were performed to determine the subgroup of variables able to give the highest predictive value for this di fferential diagnosis. A simple decision rule was built from a predictive sc ore derived by factorial discriminant analysis. Results-As previously described, the fixation defect was found in frontal r egions of interest (ROIs) in FTD and in the left temporoparietal-occipital ROIs in AD. Among the 21 variables, five were finally selected: right media n frontal, left lateral frontal, left tempoparietal, left temporoparietal-o ccipital areas, and MMSE. One hundred per cent of patients with FTD were co rrectly classified by the decision rule (20/20 patients) and 90% of patient s with AD (18/20). Conclusion-AD and FTD are differentiated by SPECT. Automatic classification based on a decision rule deduced from factorial discriminant analysis coul d enhance its performance.